Overview

Brought to you by YData

Dataset statistics

Number of variables14
Number of observations64016
Missing cells364386
Missing cells (%)40.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 MiB
Average record size in memory112.0 B

Variable types

Text5
Categorical1
Numeric6
DateTime2

Alerts

jp_sales is highly overall correlated with total_salesHigh correlation
na_sales is highly overall correlated with other_sales and 2 other fieldsHigh correlation
other_sales is highly overall correlated with na_sales and 2 other fieldsHigh correlation
pal_sales is highly overall correlated with na_sales and 2 other fieldsHigh correlation
total_sales is highly overall correlated with jp_sales and 3 other fieldsHigh correlation
critic_score has 57338 (89.6%) missing valuesMissing
total_sales has 45094 (70.4%) missing valuesMissing
na_sales has 51379 (80.3%) missing valuesMissing
jp_sales has 57290 (89.5%) missing valuesMissing
pal_sales has 51192 (80.0%) missing valuesMissing
other_sales has 48888 (76.4%) missing valuesMissing
release_date has 7051 (11.0%) missing valuesMissing
last_update has 46137 (72.1%) missing valuesMissing
total_sales has 1352 (2.1%) zerosZeros
pal_sales has 2245 (3.5%) zerosZeros
other_sales has 5165 (8.1%) zerosZeros

Reproduction

Analysis started2026-01-05 17:54:18.644120
Analysis finished2026-01-05 17:54:29.812512
Duration11.17 seconds
Software versionydata-profiling vv4.17.0
Download configurationconfig.json

Variables

img
Text

Distinct56177
Distinct (%)87.8%
Missing0
Missing (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:30.214602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length142
Median length134
Mean length42.19995
Min length24

Characters and Unicode

Total characters2701472
Distinct characters46
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56146 ?
Unique (%)87.7%

Sample

1st row/games/boxart/full_6510540AmericaFrontccc.jpg
2nd row/games/boxart/full_5563178AmericaFrontccc.jpg
3rd row/games/boxart/827563ccc.jpg
4th row/games/boxart/full_9218923AmericaFrontccc.jpg
5th row/games/boxart/full_4990510AmericaFrontccc.jpg
ValueCountFrequency (%)
games/boxart/default.jpg7810
 
12.2%
games/boxart/full_8373476americafrontccc.jpg2
 
< 0.1%
games/boxart/full_world-sports-competition_0americafront.jpg2
 
< 0.1%
games/boxart/full_2114513americafrontccc.jpg2
 
< 0.1%
games/boxart/full_753382americafrontccc.jpg2
 
< 0.1%
games/boxart/full_1110183americafrontccc.jpg2
 
< 0.1%
games/boxart/full_6050258americafrontccc.jpg2
 
< 0.1%
games/boxart/full_6167891americafrontccc.jpg2
 
< 0.1%
games/boxart/full_5798649americafrontccc.jpg2
 
< 0.1%
games/boxart/full_433462americafrontccc.jpg2
 
< 0.1%
Other values (56167)56188
87.8%
2026-01-05T23:24:30.587938image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a209321
 
7.7%
/192048
 
7.1%
c177587
 
6.6%
r158188
 
5.9%
g133223
 
4.9%
t132621
 
4.9%
o127215
 
4.7%
e125260
 
4.6%
l111807
 
4.1%
m103252
 
3.8%
Other values (36)1230950
45.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1910889
70.7%
Decimal Number343732
 
12.7%
Other Punctuation256067
 
9.5%
Uppercase Letter103965
 
3.8%
Connector Punctuation58017
 
2.1%
Dash Punctuation28802
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a209321
 
11.0%
c177587
 
9.3%
r158188
 
8.3%
g133223
 
7.0%
t132621
 
6.9%
o127215
 
6.7%
e125260
 
6.6%
l111807
 
5.9%
m103252
 
5.4%
p79349
 
4.2%
Other values (16)553066
28.9%
Decimal Number
ValueCountFrequency (%)
235605
10.4%
135394
10.3%
334963
10.2%
934903
10.2%
434884
10.1%
834743
10.1%
634583
10.1%
734545
10.0%
534471
10.0%
029641
8.6%
Uppercase Letter
ValueCountFrequency (%)
F47886
46.1%
A36907
35.5%
J10980
 
10.6%
L4096
 
3.9%
P4096
 
3.9%
Other Punctuation
ValueCountFrequency (%)
/192048
75.0%
.64018
 
25.0%
:1
 
< 0.1%
Connector Punctuation
ValueCountFrequency (%)
_58017
100.0%
Dash Punctuation
ValueCountFrequency (%)
-28802
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2014854
74.6%
Common686618
 
25.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a209321
 
10.4%
c177587
 
8.8%
r158188
 
7.9%
g133223
 
6.6%
t132621
 
6.6%
o127215
 
6.3%
e125260
 
6.2%
l111807
 
5.5%
m103252
 
5.1%
p79349
 
3.9%
Other values (21)657031
32.6%
Common
ValueCountFrequency (%)
/192048
28.0%
.64018
 
9.3%
_58017
 
8.4%
235605
 
5.2%
135394
 
5.2%
334963
 
5.1%
934903
 
5.1%
434884
 
5.1%
834743
 
5.1%
634583
 
5.0%
Other values (5)127460
18.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII2701472
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a209321
 
7.7%
/192048
 
7.1%
c177587
 
6.6%
r158188
 
5.9%
g133223
 
4.9%
t132621
 
4.9%
o127215
 
4.7%
e125260
 
4.6%
l111807
 
4.1%
m103252
 
3.8%
Other values (36)1230950
45.6%

title
Text

Distinct39798
Distinct (%)62.2%
Missing0
Missing (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:30.912539image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length147
Median length100
Mean length22.062266
Min length1

Characters and Unicode

Total characters1412338
Distinct characters155
Distinct categories18 ?
Distinct scripts6 ?
Distinct blocks10 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28464 ?
Unique (%)44.5%

Sample

1st rowGrand Theft Auto V
2nd rowGrand Theft Auto V
3rd rowGrand Theft Auto: Vice City
4th rowGrand Theft Auto V
5th rowCall of Duty: Black Ops 3
ValueCountFrequency (%)
the9848
 
4.2%
of6174
 
2.7%
23855
 
1.7%
2962
 
1.3%
no2670
 
1.1%
31536
 
0.7%
ii1286
 
0.6%
world1195
 
0.5%
game990
 
0.4%
to974
 
0.4%
Other values (23186)200829
86.4%
2026-01-05T23:24:31.483089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
168342
 
11.9%
e116672
 
8.3%
a94851
 
6.7%
o85626
 
6.1%
i76709
 
5.4%
r74801
 
5.3%
n72907
 
5.2%
t61491
 
4.4%
s55088
 
3.9%
l46196
 
3.3%
Other values (145)559655
39.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter950254
67.3%
Uppercase Letter228098
 
16.2%
Space Separator168342
 
11.9%
Other Punctuation33390
 
2.4%
Decimal Number25416
 
1.8%
Dash Punctuation4670
 
0.3%
Open Punctuation862
 
0.1%
Close Punctuation862
 
0.1%
Math Symbol294
 
< 0.1%
Final Punctuation47
 
< 0.1%
Other values (8)103
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e116672
12.3%
a94851
10.0%
o85626
 
9.0%
i76709
 
8.1%
r74801
 
7.9%
n72907
 
7.7%
t61491
 
6.5%
s55088
 
5.8%
l46196
 
4.9%
u39590
 
4.2%
Other values (33)226323
23.8%
Uppercase Letter
ValueCountFrequency (%)
S24705
 
10.8%
T18234
 
8.0%
C14508
 
6.4%
A13772
 
6.0%
M13724
 
6.0%
D13578
 
6.0%
P11794
 
5.2%
B11705
 
5.1%
R11422
 
5.0%
F9874
 
4.3%
Other values (18)84782
37.2%
Other Letter
ValueCountFrequency (%)
2
 
8.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
1
 
4.0%
Other values (14)14
56.0%
Other Punctuation
ValueCountFrequency (%)
:20778
62.2%
'4021
 
12.0%
!3013
 
9.0%
.2909
 
8.7%
&1182
 
3.5%
/488
 
1.5%
,408
 
1.2%
?212
 
0.6%
*186
 
0.6%
;64
 
0.2%
Other values (8)129
 
0.4%
Decimal Number
ValueCountFrequency (%)
27598
29.9%
05548
21.8%
13353
13.2%
32616
 
10.3%
41611
 
6.3%
91242
 
4.9%
51168
 
4.6%
6846
 
3.3%
7740
 
2.9%
8694
 
2.7%
Other Symbol
ValueCountFrequency (%)
7
31.8%
®6
27.3%
°3
13.6%
2
 
9.1%
©1
 
4.5%
1
 
4.5%
1
 
4.5%
1
 
4.5%
Math Symbol
ValueCountFrequency (%)
+210
71.4%
~78
 
26.5%
=3
 
1.0%
1
 
0.3%
×1
 
0.3%
<1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-4575
98.0%
69
 
1.5%
26
 
0.6%
Open Punctuation
ValueCountFrequency (%)
(842
97.7%
[20
 
2.3%
Close Punctuation
ValueCountFrequency (%)
)842
97.7%
]20
 
2.3%
Modifier Symbol
ValueCountFrequency (%)
´4
57.1%
^3
42.9%
Other Number
ValueCountFrequency (%)
²2
66.7%
³1
33.3%
Format
ValueCountFrequency (%)
1
50.0%
1
50.0%
Space Separator
ValueCountFrequency (%)
168342
100.0%
Final Punctuation
ValueCountFrequency (%)
47
100.0%
Connector Punctuation
ValueCountFrequency (%)
_25
100.0%
Currency Symbol
ValueCountFrequency (%)
$13
100.0%
Initial Punctuation
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1178345
83.4%
Common233962
 
16.6%
Hiragana12
 
< 0.1%
Han8
 
< 0.1%
Greek7
 
< 0.1%
Katakana4
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e116672
 
9.9%
a94851
 
8.0%
o85626
 
7.3%
i76709
 
6.5%
r74801
 
6.3%
n72907
 
6.2%
t61491
 
5.2%
s55088
 
4.7%
l46196
 
3.9%
u39590
 
3.4%
Other values (60)454414
38.6%
Common
ValueCountFrequency (%)
168342
72.0%
:20778
 
8.9%
27598
 
3.2%
05548
 
2.4%
-4575
 
2.0%
'4021
 
1.7%
13353
 
1.4%
!3013
 
1.3%
.2909
 
1.2%
32616
 
1.1%
Other values (51)11209
 
4.8%
Hiragana
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Han
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Greek
ValueCountFrequency (%)
α7
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII1411936
> 99.9%
None240
 
< 0.1%
Punctuation125
 
< 0.1%
Hiragana12
 
< 0.1%
CJK8
 
< 0.1%
Letterlike Symbols7
 
< 0.1%
Misc Symbols4
 
< 0.1%
Katakana4
 
< 0.1%
Arrows1
 
< 0.1%
Specials1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
168342
 
11.9%
e116672
 
8.3%
a94851
 
6.7%
o85626
 
6.1%
i76709
 
5.4%
r74801
 
5.3%
n72907
 
5.2%
t61491
 
4.4%
s55088
 
3.9%
l46196
 
3.3%
Other values (79)559253
39.6%
None
ValueCountFrequency (%)
é116
48.3%
26
 
10.8%
ö13
 
5.4%
ú12
 
5.0%
α7
 
2.9%
®6
 
2.5%
ä6
 
2.5%
ü5
 
2.1%
ë5
 
2.1%
·5
 
2.1%
Other values (22)39
 
16.2%
Punctuation
ValueCountFrequency (%)
69
55.2%
47
37.6%
6
 
4.8%
2
 
1.6%
1
 
0.8%
Letterlike Symbols
ValueCountFrequency (%)
7
100.0%
Hiragana
ValueCountFrequency (%)
2
16.7%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
1
8.3%
Misc Symbols
ValueCountFrequency (%)
2
50.0%
1
25.0%
1
25.0%
Katakana
ValueCountFrequency (%)
1
25.0%
1
25.0%
1
25.0%
1
25.0%
Arrows
ValueCountFrequency (%)
1
100.0%
CJK
ValueCountFrequency (%)
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
1
12.5%
Specials
ValueCountFrequency (%)
1
100.0%

console
Text

Distinct81
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:31.633767image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.713103
Min length2

Characters and Unicode

Total characters173682
Distinct characters50
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowPS3
2nd rowPS4
3rd rowPS2
4th rowX360
5th rowPS4
ValueCountFrequency (%)
pc12617
19.7%
ps23565
 
5.6%
ds3288
 
5.1%
ps42878
 
4.5%
ps2707
 
4.2%
ns2337
 
3.7%
xbl2120
 
3.3%
psn2004
 
3.1%
xone1963
 
3.1%
ps31905
 
3.0%
Other values (71)28632
44.7%
2026-01-05T23:24:31.885172image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P31659
18.2%
S31273
18.0%
C15487
 
8.9%
X8191
 
4.7%
N8088
 
4.7%
D6524
 
3.8%
B6463
 
3.7%
i6401
 
3.7%
G5696
 
3.3%
35143
 
3.0%
Other values (40)48757
28.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter135797
78.2%
Decimal Number19105
 
11.0%
Lowercase Letter18780
 
10.8%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
P31659
23.3%
S31273
23.0%
C15487
11.4%
X8191
 
6.0%
N8088
 
6.0%
D6524
 
4.8%
B6463
 
4.8%
G5696
 
4.2%
A4785
 
3.5%
W4245
 
3.1%
Other values (13)13386
9.9%
Lowercase Letter
ValueCountFrequency (%)
i6401
34.1%
n3677
19.6%
e2969
15.8%
l2276
 
12.1%
d1051
 
5.6%
r516
 
2.7%
s464
 
2.5%
x459
 
2.4%
u412
 
2.2%
t134
 
0.7%
Other values (8)421
 
2.2%
Decimal Number
ValueCountFrequency (%)
35143
26.9%
24146
21.7%
43305
17.3%
03001
15.7%
62666
14.0%
5721
 
3.8%
860
 
0.3%
759
 
0.3%
14
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
Latin154577
89.0%
Common19105
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P31659
20.5%
S31273
20.2%
C15487
10.0%
X8191
 
5.3%
N8088
 
5.2%
D6524
 
4.2%
B6463
 
4.2%
i6401
 
4.1%
G5696
 
3.7%
A4785
 
3.1%
Other values (31)30010
19.4%
Common
ValueCountFrequency (%)
35143
26.9%
24146
21.7%
43305
17.3%
03001
15.7%
62666
14.0%
5721
 
3.8%
860
 
0.3%
759
 
0.3%
14
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII173682
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P31659
18.2%
S31273
18.0%
C15487
 
8.9%
X8191
 
4.7%
N8088
 
4.7%
D6524
 
3.8%
B6463
 
3.7%
i6401
 
3.7%
G5696
 
3.3%
35143
 
3.0%
Other values (40)48757
28.1%

genre
Categorical

Distinct20
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size500.3 KiB
Misc
9304 
Action
8557 
Adventure
6260 
Role-Playing
5721 
Sports
5586 
Other values (15)
28588 

Length

Max length16
Median length10
Mean length7.4658523
Min length3

Characters and Unicode

Total characters477934
Distinct characters36
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAction
2nd rowAction
3rd rowAction
4th rowAction
5th rowShooter

Common Values

ValueCountFrequency (%)
Misc9304
14.5%
Action8557
13.4%
Adventure6260
9.8%
Role-Playing5721
8.9%
Sports5586
8.7%
Shooter5410
8.5%
Platform4001
6.2%
Strategy3685
 
5.8%
Puzzle3521
 
5.5%
Racing3425
 
5.4%
Other values (10)8546
13.3%

Length

2026-01-05T23:24:32.025700image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
misc9304
14.4%
action8557
13.3%
adventure6260
9.7%
role-playing5721
8.9%
sports5586
8.7%
shooter5410
8.4%
platform4001
6.2%
strategy3685
 
5.7%
puzzle3521
 
5.5%
racing3425
 
5.3%
Other values (12)9072
14.1%

Most occurring characters

ValueCountFrequency (%)
t46649
 
9.8%
i40759
 
8.5%
o40301
 
8.4%
e35137
 
7.4%
n33297
 
7.0%
r27003
 
5.6%
c23495
 
4.9%
l23108
 
4.8%
a20755
 
4.3%
A18571
 
3.9%
Other values (26)168859
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter397440
83.2%
Uppercase Letter72370
 
15.1%
Dash Punctuation7598
 
1.6%
Space Separator526
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t46649
11.7%
i40759
10.3%
o40301
10.1%
e35137
 
8.8%
n33297
 
8.4%
r27003
 
6.8%
c23495
 
5.9%
l23108
 
5.8%
a20755
 
5.2%
g17565
 
4.4%
Other values (12)89371
22.5%
Uppercase Letter
ValueCountFrequency (%)
A18571
25.7%
S17859
24.7%
P13394
18.5%
M9831
13.6%
R9146
12.6%
F2367
 
3.3%
V493
 
0.7%
N493
 
0.7%
O115
 
0.2%
E35
 
< 0.1%
Other values (2)66
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-7598
100.0%
Space Separator
ValueCountFrequency (%)
526
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin469810
98.3%
Common8124
 
1.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t46649
 
9.9%
i40759
 
8.7%
o40301
 
8.6%
e35137
 
7.5%
n33297
 
7.1%
r27003
 
5.7%
c23495
 
5.0%
l23108
 
4.9%
a20755
 
4.4%
A18571
 
4.0%
Other values (24)160735
34.2%
Common
ValueCountFrequency (%)
-7598
93.5%
526
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII477934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t46649
 
9.8%
i40759
 
8.5%
o40301
 
8.4%
e35137
 
7.4%
n33297
 
7.0%
r27003
 
5.6%
c23495
 
4.9%
l23108
 
4.8%
a20755
 
4.3%
A18571
 
3.9%
Other values (26)168859
35.3%
Distinct3383
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:32.313536image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length49
Median length40
Mean length11.121376
Min length2

Characters and Unicode

Total characters711946
Distinct characters86
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1227 ?
Unique (%)1.9%

Sample

1st rowRockstar Games
2nd rowRockstar Games
3rd rowRockstar Games
4th rowRockstar Games
5th rowActivision
ValueCountFrequency (%)
unknown8845
 
8.7%
entertainment5167
 
5.1%
games4679
 
4.6%
interactive3778
 
3.7%
sega2213
 
2.2%
bandai1868
 
1.8%
namco1763
 
1.7%
sony1735
 
1.7%
konami1700
 
1.7%
arts1672
 
1.6%
Other values (3519)67927
67.0%
2026-01-05T23:24:32.671726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n72158
 
10.1%
e57006
 
8.0%
t54685
 
7.7%
o52038
 
7.3%
a49154
 
6.9%
i46753
 
6.6%
r37558
 
5.3%
37292
 
5.2%
s28635
 
4.0%
m24320
 
3.4%
Other values (76)252347
35.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter553352
77.7%
Uppercase Letter115358
 
16.2%
Space Separator37332
 
5.2%
Decimal Number3358
 
0.5%
Other Punctuation2087
 
0.3%
Dash Punctuation423
 
0.1%
Math Symbol11
 
< 0.1%
Open Punctuation9
 
< 0.1%
Close Punctuation9
 
< 0.1%
Connector Punctuation6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n72158
13.0%
e57006
10.3%
t54685
9.9%
o52038
9.4%
a49154
8.9%
i46753
8.4%
r37558
 
6.8%
s28635
 
5.2%
m24320
 
4.4%
c22995
 
4.2%
Other values (19)108050
19.5%
Uppercase Letter
ValueCountFrequency (%)
S14331
12.4%
U11076
 
9.6%
E11074
 
9.6%
A9020
 
7.8%
I7668
 
6.6%
G7295
 
6.3%
C6945
 
6.0%
N5511
 
4.8%
M5455
 
4.7%
T5227
 
4.5%
Other values (17)31756
27.5%
Decimal Number
ValueCountFrequency (%)
5800
23.8%
3800
23.8%
2658
19.6%
0371
11.0%
1343
10.2%
7164
 
4.9%
4103
 
3.1%
973
 
2.2%
841
 
1.2%
65
 
0.1%
Other Punctuation
ValueCountFrequency (%)
.1503
72.0%
,229
 
11.0%
&110
 
5.3%
!106
 
5.1%
'71
 
3.4%
/63
 
3.0%
*2
 
0.1%
@2
 
0.1%
:1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
37292
99.9%
 40
 
0.1%
Open Punctuation
ValueCountFrequency (%)
(8
88.9%
[1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
)8
88.9%
]1
 
11.1%
Math Symbol
ValueCountFrequency (%)
+6
54.5%
~5
45.5%
Dash Punctuation
ValueCountFrequency (%)
-423
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%
Modifier Symbol
ValueCountFrequency (%)
`1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin668710
93.9%
Common43236
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
n72158
 
10.8%
e57006
 
8.5%
t54685
 
8.2%
o52038
 
7.8%
a49154
 
7.4%
i46753
 
7.0%
r37558
 
5.6%
s28635
 
4.3%
m24320
 
3.6%
c22995
 
3.4%
Other values (46)223408
33.4%
Common
ValueCountFrequency (%)
37292
86.3%
.1503
 
3.5%
5800
 
1.9%
3800
 
1.9%
2658
 
1.5%
-423
 
1.0%
0371
 
0.9%
1343
 
0.8%
,229
 
0.5%
7164
 
0.4%
Other values (20)653
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII711901
> 99.9%
None45
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n72158
 
10.1%
e57006
 
8.0%
t54685
 
7.7%
o52038
 
7.3%
a49154
 
6.9%
i46753
 
6.6%
r37558
 
5.3%
37292
 
5.2%
s28635
 
4.0%
m24320
 
3.4%
Other values (71)252302
35.4%
None
ValueCountFrequency (%)
 40
88.9%
é2
 
4.4%
Ü1
 
2.2%
ä1
 
2.2%
ó1
 
2.2%
Distinct8862
Distinct (%)13.8%
Missing17
Missing (%)< 0.1%
Memory size500.3 KiB
2026-01-05T23:24:32.877341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length68
Median length52
Mean length12.73084
Min length2

Characters and Unicode

Total characters814761
Distinct characters94
Distinct categories13 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3933 ?
Unique (%)6.1%

Sample

1st rowRockstar North
2nd rowRockstar North
3rd rowRockstar North
4th rowRockstar North
5th rowTreyarch
ValueCountFrequency (%)
games6130
 
5.2%
unknown4447
 
3.8%
entertainment3551
 
3.0%
studios3516
 
3.0%
software2861
 
2.4%
interactive2128
 
1.8%
corporation1675
 
1.4%
inc1608
 
1.4%
studio1432
 
1.2%
konami1190
 
1.0%
Other values (7654)89227
75.8%
2026-01-05T23:24:33.255565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e67378
 
8.3%
a61367
 
7.5%
n61084
 
7.5%
o58996
 
7.2%
t55262
 
6.8%
53630
 
6.6%
i51892
 
6.4%
r40751
 
5.0%
s33703
 
4.1%
m26784
 
3.3%
Other values (84)303914
37.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter616269
75.6%
Uppercase Letter134228
 
16.5%
Space Separator53780
 
6.6%
Other Punctuation6326
 
0.8%
Decimal Number3082
 
0.4%
Dash Punctuation952
 
0.1%
Open Punctuation47
 
< 0.1%
Close Punctuation47
 
< 0.1%
Math Symbol15
 
< 0.1%
Connector Punctuation10
 
< 0.1%
Other values (3)5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e67378
10.9%
a61367
10.0%
n61084
9.9%
o58996
9.6%
t55262
 
9.0%
i51892
 
8.4%
r40751
 
6.6%
s33703
 
5.5%
m26784
 
4.3%
l20493
 
3.3%
Other values (23)138559
22.5%
Uppercase Letter
ValueCountFrequency (%)
S20242
15.1%
C10665
 
7.9%
G9736
 
7.3%
E9280
 
6.9%
A7898
 
5.9%
I7584
 
5.7%
T7408
 
5.5%
U6143
 
4.6%
M5761
 
4.3%
B5735
 
4.3%
Other values (18)43776
32.6%
Other Punctuation
ValueCountFrequency (%)
.3984
63.0%
,1039
 
16.4%
/496
 
7.8%
'431
 
6.8%
&262
 
4.1%
!71
 
1.1%
:30
 
0.5%
?4
 
0.1%
@4
 
0.1%
*4
 
0.1%
Decimal Number
ValueCountFrequency (%)
1597
19.4%
2502
16.3%
3426
13.8%
5415
13.5%
0258
8.4%
7254
8.2%
4251
8.1%
9179
 
5.8%
8101
 
3.3%
699
 
3.2%
Space Separator
ValueCountFrequency (%)
53630
99.7%
 150
 
0.3%
Open Punctuation
ValueCountFrequency (%)
(46
97.9%
[1
 
2.1%
Close Punctuation
ValueCountFrequency (%)
)46
97.9%
]1
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
-952
100.0%
Math Symbol
ValueCountFrequency (%)
+15
100.0%
Connector Punctuation
ValueCountFrequency (%)
_10
100.0%
Other Number
ValueCountFrequency (%)
³2
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%
Modifier Symbol
ValueCountFrequency (%)
`1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin750497
92.1%
Common64264
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e67378
 
9.0%
a61367
 
8.2%
n61084
 
8.1%
o58996
 
7.9%
t55262
 
7.4%
i51892
 
6.9%
r40751
 
5.4%
s33703
 
4.5%
m26784
 
3.6%
l20493
 
2.7%
Other values (51)272787
36.3%
Common
ValueCountFrequency (%)
53630
83.5%
.3984
 
6.2%
,1039
 
1.6%
-952
 
1.5%
1597
 
0.9%
2502
 
0.8%
/496
 
0.8%
'431
 
0.7%
3426
 
0.7%
5415
 
0.6%
Other values (23)1792
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII814586
> 99.9%
None173
 
< 0.1%
Punctuation2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e67378
 
8.3%
a61367
 
7.5%
n61084
 
7.5%
o58996
 
7.2%
t55262
 
6.8%
53630
 
6.6%
i51892
 
6.4%
r40751
 
5.0%
s33703
 
4.1%
m26784
 
3.3%
Other values (72)303739
37.3%
None
ValueCountFrequency (%)
 150
86.7%
ç5
 
2.9%
Ü3
 
1.7%
ø3
 
1.7%
é3
 
1.7%
Ã2
 
1.2%
³2
 
1.2%
ä2
 
1.2%
ý1
 
0.6%
ë1
 
0.6%
Punctuation
ValueCountFrequency (%)
2
100.0%

critic_score
Real number (ℝ)

Missing 

Distinct89
Distinct (%)1.3%
Missing57338
Missing (%)89.6%
Infinite0
Infinite (%)0.0%
Mean7.2204403
Minimum1
Maximum10
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:33.358194image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.4
Q16.4
median7.5
Q38.3
95-th percentile9.1
Maximum10
Range9
Interquartile range (IQR)1.9

Descriptive statistics

Standard deviation1.4570656
Coefficient of variation (CV)0.20179734
Kurtosis0.828948
Mean7.2204403
Median Absolute Deviation (MAD)0.9
Skewness-0.91063686
Sum48218.1
Variance2.1230403
MonotonicityNot monotonic
2026-01-05T23:24:33.471889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8355
 
0.6%
7332
 
0.5%
7.5277
 
0.4%
8.5214
 
0.3%
9207
 
0.3%
8.3203
 
0.3%
6202
 
0.3%
7.9196
 
0.3%
8.2192
 
0.3%
8.1190
 
0.3%
Other values (79)4310
 
6.7%
(Missing)57338
89.6%
ValueCountFrequency (%)
12
 
< 0.1%
1.21
 
< 0.1%
1.31
 
< 0.1%
1.41
 
< 0.1%
1.54
 
< 0.1%
1.72
 
< 0.1%
1.81
 
< 0.1%
1.92
 
< 0.1%
211
< 0.1%
2.12
 
< 0.1%
ValueCountFrequency (%)
1016
 
< 0.1%
9.93
 
< 0.1%
9.83
 
< 0.1%
9.717
 
< 0.1%
9.626
 
< 0.1%
9.546
0.1%
9.441
0.1%
9.376
0.1%
9.282
0.1%
9.195
0.1%

total_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct482
Distinct (%)2.5%
Missing45094
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean0.34911267
Minimum0
Maximum20.32
Zeros1352
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:33.583089image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.03
median0.12
Q30.34
95-th percentile1.37
Maximum20.32
Range20.32
Interquartile range (IQR)0.31

Descriptive statistics

Standard deviation0.8074622
Coefficient of variation (CV)2.3128986
Kurtosis125.55245
Mean0.34911267
Median Absolute Deviation (MAD)0.1
Skewness8.7753333
Sum6605.91
Variance0.6519952
MonotonicityDecreasing
2026-01-05T23:24:33.705329image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011366
 
2.1%
01352
 
2.1%
0.021228
 
1.9%
0.03941
 
1.5%
0.04768
 
1.2%
0.05684
 
1.1%
0.06631
 
1.0%
0.07572
 
0.9%
0.08514
 
0.8%
0.09442
 
0.7%
Other values (472)10424
 
16.3%
(Missing)45094
70.4%
ValueCountFrequency (%)
01352
2.1%
0.011366
2.1%
0.021228
1.9%
0.03941
1.5%
0.04768
1.2%
0.05684
1.1%
0.06631
1.0%
0.07572
0.9%
0.08514
 
0.8%
0.09442
 
0.7%
ValueCountFrequency (%)
20.321
< 0.1%
19.391
< 0.1%
16.151
< 0.1%
15.861
< 0.1%
15.091
< 0.1%
14.821
< 0.1%
14.741
< 0.1%
13.941
< 0.1%
13.861
< 0.1%
13.81
< 0.1%

na_sales
Real number (ℝ)

High correlation  Missing 

Distinct320
Distinct (%)2.5%
Missing51379
Missing (%)80.3%
Infinite0
Infinite (%)0.0%
Mean0.26474005
Minimum0
Maximum9.76
Zeros280
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:34.089562image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.01
Q10.05
median0.12
Q30.28
95-th percentile0.99
Maximum9.76
Range9.76
Interquartile range (IQR)0.23

Descriptive statistics

Standard deviation0.4947866
Coefficient of variation (CV)1.8689526
Kurtosis78.62858
Mean0.26474005
Median Absolute Deviation (MAD)0.09
Skewness6.8983729
Sum3345.52
Variance0.24481378
MonotonicityNot monotonic
2026-01-05T23:24:34.205235image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.04651
 
1.0%
0.01649
 
1.0%
0.02640
 
1.0%
0.03628
 
1.0%
0.05617
 
1.0%
0.06556
 
0.9%
0.07525
 
0.8%
0.08471
 
0.7%
0.09445
 
0.7%
0.1408
 
0.6%
Other values (310)7047
 
11.0%
(Missing)51379
80.3%
ValueCountFrequency (%)
0280
0.4%
0.01649
1.0%
0.02640
1.0%
0.03628
1.0%
0.04651
1.0%
0.05617
1.0%
0.06556
0.9%
0.07525
0.8%
0.08471
0.7%
0.09445
0.7%
ValueCountFrequency (%)
9.761
< 0.1%
9.071
< 0.1%
9.061
< 0.1%
8.541
< 0.1%
8.411
< 0.1%
8.271
< 0.1%
7.081
< 0.1%
6.991
< 0.1%
6.81
< 0.1%
6.761
< 0.1%

jp_sales
Real number (ℝ)

High correlation  Missing 

Distinct121
Distinct (%)1.8%
Missing57290
Missing (%)89.5%
Infinite0
Infinite (%)0.0%
Mean0.1022807
Minimum0
Maximum2.13
Zeros420
Zeros (%)0.7%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:34.316869image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.04
Q30.12
95-th percentile0.39
Maximum2.13
Range2.13
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.16881138
Coefficient of variation (CV)1.6504714
Kurtosis30.528417
Mean0.1022807
Median Absolute Deviation (MAD)0.03
Skewness4.4904062
Sum687.94
Variance0.028497281
MonotonicityNot monotonic
2026-01-05T23:24:34.449056image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.011137
 
1.8%
0.02845
 
1.3%
0.03619
 
1.0%
0.04452
 
0.7%
0420
 
0.7%
0.05329
 
0.5%
0.06301
 
0.5%
0.07248
 
0.4%
0.08212
 
0.3%
0.09168
 
0.3%
Other values (111)1995
 
3.1%
(Missing)57290
89.5%
ValueCountFrequency (%)
0420
 
0.7%
0.011137
1.8%
0.02845
1.3%
0.03619
1.0%
0.04452
 
0.7%
0.05329
 
0.5%
0.06301
 
0.5%
0.07248
 
0.4%
0.08212
 
0.3%
0.09168
 
0.3%
ValueCountFrequency (%)
2.132
< 0.1%
2.052
< 0.1%
1.871
< 0.1%
1.821
< 0.1%
1.692
< 0.1%
1.51
< 0.1%
1.481
< 0.1%
1.451
< 0.1%
1.442
< 0.1%
1.431
< 0.1%

pal_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct256
Distinct (%)2.0%
Missing51192
Missing (%)80.0%
Infinite0
Infinite (%)0.0%
Mean0.14947208
Minimum0
Maximum9.85
Zeros2245
Zeros (%)3.5%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:34.589352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.01
median0.04
Q30.14
95-th percentile0.59
Maximum9.85
Range9.85
Interquartile range (IQR)0.13

Descriptive statistics

Standard deviation0.39265263
Coefficient of variation (CV)2.6269295
Kurtosis147.20484
Mean0.14947208
Median Absolute Deviation (MAD)0.04
Skewness9.5869097
Sum1916.83
Variance0.15417608
MonotonicityNot monotonic
2026-01-05T23:24:34.709487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
02245
 
3.5%
0.011635
 
2.6%
0.021290
 
2.0%
0.03959
 
1.5%
0.04717
 
1.1%
0.05552
 
0.9%
0.06422
 
0.7%
0.07358
 
0.6%
0.08297
 
0.5%
0.09274
 
0.4%
Other values (246)4075
 
6.4%
(Missing)51192
80.0%
ValueCountFrequency (%)
02245
3.5%
0.011635
2.6%
0.021290
2.0%
0.03959
1.5%
0.04717
 
1.1%
0.05552
 
0.9%
0.06422
 
0.7%
0.07358
 
0.6%
0.08297
 
0.5%
0.09274
 
0.4%
ValueCountFrequency (%)
9.851
< 0.1%
9.711
< 0.1%
8.641
< 0.1%
7.951
< 0.1%
6.871
< 0.1%
6.461
< 0.1%
6.212
< 0.1%
6.051
< 0.1%
5.881
< 0.1%
5.781
< 0.1%

other_sales
Real number (ℝ)

High correlation  Missing  Zeros 

Distinct133
Distinct (%)0.9%
Missing48888
Missing (%)76.4%
Infinite0
Infinite (%)0.0%
Mean0.043040719
Minimum0
Maximum3.12
Zeros5165
Zeros (%)8.1%
Negative0
Negative (%)0.0%
Memory size500.3 KiB
2026-01-05T23:24:34.830084image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.01
Q30.03
95-th percentile0.18
Maximum3.12
Range3.12
Interquartile range (IQR)0.03

Descriptive statistics

Standard deviation0.1266435
Coefficient of variation (CV)2.9424113
Kurtosis144.48453
Mean0.043040719
Median Absolute Deviation (MAD)0.01
Skewness9.7945504
Sum651.12
Variance0.016038575
MonotonicityNot monotonic
2026-01-05T23:24:34.966766image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05165
 
8.1%
0.013609
 
5.6%
0.021690
 
2.6%
0.03939
 
1.5%
0.04628
 
1.0%
0.05475
 
0.7%
0.06364
 
0.6%
0.07327
 
0.5%
0.08215
 
0.3%
0.09182
 
0.3%
Other values (123)1534
 
2.4%
(Missing)48888
76.4%
ValueCountFrequency (%)
05165
8.1%
0.013609
5.6%
0.021690
 
2.6%
0.03939
 
1.5%
0.04628
 
1.0%
0.05475
 
0.7%
0.06364
 
0.6%
0.07327
 
0.5%
0.08215
 
0.3%
0.09182
 
0.3%
ValueCountFrequency (%)
3.121
< 0.1%
3.021
< 0.1%
2.931
< 0.1%
2.461
< 0.1%
2.441
< 0.1%
2.281
< 0.1%
2.261
< 0.1%
2.121
< 0.1%
2.051
< 0.1%
1.821
< 0.1%

release_date
Date

Missing 

Distinct7922
Distinct (%)13.9%
Missing7051
Missing (%)11.0%
Memory size500.3 KiB
Minimum1971-12-03 00:00:00
Maximum2024-12-31 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-05T23:24:35.209044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:35.396007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

last_update
Date

Missing 

Distinct1545
Distinct (%)8.6%
Missing46137
Missing (%)72.1%
Memory size500.3 KiB
Minimum2017-11-28 00:00:00
Maximum2024-01-28 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2026-01-05T23:24:35.539602image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:35.673298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Interactions

2026-01-05T23:24:28.131707image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:24.529117image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.346787image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.275425image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.884996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.474439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.227327image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:24.690846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.628639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.361474image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.992596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.562483image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.343923image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:24.827073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.763889image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.466614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.095274image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.659966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.452447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:24.951498image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.888036image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.563210image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.187910image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.751479image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.571034image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.103631image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.006634image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.672863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.280482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.905559image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.687120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:25.216158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.153219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:26.778463image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:27.379848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2026-01-05T23:24:28.030082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2026-01-05T23:24:35.772939image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
critic_scoregenrejp_salesna_salesother_salespal_salestotal_sales
critic_score1.0000.0640.1330.3680.3090.3260.338
genre0.0641.0000.0700.0280.0220.0160.036
jp_sales0.1330.0701.0000.001-0.113-0.0000.546
na_sales0.3680.0280.0011.0000.7580.6520.926
other_sales0.3090.022-0.1130.7581.0000.7810.867
pal_sales0.3260.016-0.0000.6520.7811.0000.827
total_sales0.3380.0360.5460.9260.8670.8271.000

Missing values

2026-01-05T23:24:28.927943image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2026-01-05T23:24:29.132648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2026-01-05T23:24:29.610293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

imgtitleconsolegenrepublisherdevelopercritic_scoretotal_salesna_salesjp_salespal_salesother_salesrelease_datelast_update
0/games/boxart/full_6510540AmericaFrontccc.jpgGrand Theft Auto VPS3ActionRockstar GamesRockstar North9.420.326.370.999.853.122013-09-17NaN
1/games/boxart/full_5563178AmericaFrontccc.jpgGrand Theft Auto VPS4ActionRockstar GamesRockstar North9.719.396.060.609.713.022014-11-182018-01-03
2/games/boxart/827563ccc.jpgGrand Theft Auto: Vice CityPS2ActionRockstar GamesRockstar North9.616.158.410.475.491.782002-10-28NaN
3/games/boxart/full_9218923AmericaFrontccc.jpgGrand Theft Auto VX360ActionRockstar GamesRockstar NorthNaN15.869.060.065.331.422013-09-17NaN
4/games/boxart/full_4990510AmericaFrontccc.jpgCall of Duty: Black Ops 3PS4ShooterActivisionTreyarch8.115.096.180.416.052.442015-11-062018-01-14
5/games/boxart/full_call-of-duty-modern-warfare-3_517AmericaFront.jpgCall of Duty: Modern Warfare 3X360ShooterActivisionInfinity Ward8.714.829.070.134.291.332011-11-08NaN
6/games/boxart/full_call-of-duty-black-ops_5AmericaFront.jpgCall of Duty: Black OpsX360ShooterActivisionTreyarch8.814.749.760.113.731.142010-11-09NaN
7/games/boxart/full_4653215AmericaFrontccc.jpgRed Dead Redemption 2PS4Action-AdventureRockstar GamesRockstar Games9.813.945.260.216.212.262018-10-262018-11-02
8/games/boxart/full_1977964AmericaFrontccc.jpgCall of Duty: Black Ops IIX360ShooterActivisionTreyarch8.413.868.270.074.321.202012-11-132018-04-07
9/games/boxart/full_4649679AmericaFrontccc.pngCall of Duty: Black Ops IIPS3ShooterActivisionTreyarch8.013.804.990.655.882.282012-11-132018-04-07
imgtitleconsolegenrepublisherdevelopercritic_scoretotal_salesna_salesjp_salespal_salesother_salesrelease_datelast_update
64006/games/boxart/default.jpgWithout WithinPCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2015-01-222018-12-25
64007/games/boxart/default.jpgWithout Within 2PCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2015-11-092018-12-25
64008/games/boxart/default.jpgWithout Within 3PCVisual NovelInvertMouseInvertMouseNaNNaNNaNNaNNaNNaN2018-05-032018-12-25
64009/games/boxart/full_2129671JapanFrontccc.jpgWorld End SyndromePSVVisual NovelArc System WorksArc System WorksNaNNaNNaNNaNNaNNaN2018-04-262019-04-03
64010/games/boxart/full_2294305JapanFrontccc.jpgWorld End SyndromePS4Visual NovelArc System WorksArc System WorksNaNNaNNaNNaNNaNNaN2018-04-262019-04-03
64011/games/boxart/full_2779838AmericaFrontccc.jpgXBlaze Lost: MemoriesPCVisual NovelAksys GamesArc System WorksNaNNaNNaNNaNNaNNaN2016-08-112019-01-28
64012/games/boxart/full_8031506AmericaFrontccc.jpgYoru, TomosuPS4Visual NovelNippon Ichi SoftwareNippon Ichi SoftwareNaNNaNNaNNaNNaNNaN2020-07-302020-05-09
64013/games/boxart/full_6553045AmericaFrontccc.jpgYoru, TomosuNSVisual NovelNippon Ichi SoftwareNippon Ichi SoftwareNaNNaNNaNNaNNaNNaN2020-07-302020-05-09
64014/games/boxart/full_6012940JapanFrontccc.pngYunohana SpRING! ~Mellow Times~NSVisual NovelIdea FactoryOtomateNaNNaNNaNNaNNaNNaN2019-02-282019-02-24
64015/games/boxart/default.jpgYurukill: The Calumniation GamesPS4Visual NovelUnknownG.rev Ltd.NaNNaNNaNNaNNaNNaNNaN2023-09-29